1. Background Field
Embodiments of the subject matter described herein are related generally to tracking and mapping, and more particularly to vision based mapping and tracking with a mobile device.
2. Relevant Background
In recent years, model-based tracking has become state-of-the-art on mobile devices. Natural feature detection and tracking of a-priori known well-textured images in real-time have been shown by multiple groups and these techniques have found their way into commercial applications and software development kits.
Mapping of a-priori unknown scenes in full three-dimensions and tracking in six degree of freedom (6DOF) with a monocular camera still remains a difficult task, particularly on mobile devices, such as cellular phones or smart phones. Classical Extended Kalman filter (EKF) based approaches known from the robotics community are currently computationally infeasible. Only the well-known Parallel Tracking and Mapping (PTAM) system has been shown to run as a prototype on current smart phones. The PTAM mapping method, however, is based on bundle adjustment techniques, which scale badly with increasing map sizes due to high computational demands.